Why are neural networks always trained "by themselves"?
The way children learn is in many ways supervised. It is true that certain abilities are there genetically (visual system, object recognition, to large extent voice recognition), but a lot of human experience is gained as a result of response, either from the environment or from the mentor (parent, teacher, etc).

Social interaction is possible only when a human already learned a lot (things we consider trivial, but in fact pretty complex), in this sense this is equivalent to AlphaGo learning to play Go by playing with a copy network. NNs that can only perform object or voice recognition can't interact, they are too primitive for this. And a nearly all of todays AI is on this stage right now.

However, it is true that NN learning is much less efficient than human learning and current models are far from AGI. I think RL is the closest area that studies real multi-agent environments.